Literature DB >> 15358394

The case-combined-control design was efficient in detecting gene-environment interactions.

N Andrieu1, A M Goldstein.   

Abstract

OBJECTIVE: The interest in studying gene-environment (GxE) interaction is increasing for complex diseases. A design combining both related and unrelated controls (e.g., population-based and siblings) is proposed to increase the power to detect GxE interaction. STUDY DESIGN AND
SETTING: We used simulations to assess the efficiency of the case-combined-control design relative to a classical case-control study under a variety of assumptions.
RESULTS: The case-combined-control design appears more efficient and feasible than a classical case-control study for detecting interaction involving rare exposures and/or genetic factors. The number of available sibling controls per case and the frequencies of the risk factors are the most important parameters for determining relative efficiency. Relative efficiencies decrease as the frequency of the gene (G) increases. A positive correlation in exposure (E) between siblings decreases relative efficiency.
CONCLUSIONS: Although the case-combined-control design may not be efficient for common genes with moderate effects, it appears to be a useful alternative in certain situations where classical approaches remain unrealistic.

Mesh:

Year:  2004        PMID: 15358394     DOI: 10.1016/j.jclinepi.2003.11.014

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  6 in total

1.  Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.

Authors:  Alisa M Goldstein; Marie-Gabrielle Dondon; Nadine Andrieu
Journal:  Int J Epidemiol       Date:  2006-03-23       Impact factor: 7.196

2.  Genotype-environment interactions and their translational implications.

Authors:  Tesfaye M Baye; Tilahun Abebe; Russell A Wilke
Journal:  Per Med       Date:  2011-01       Impact factor: 2.512

Review 3.  Challenges and opportunities in genome-wide environmental interaction (GWEI) studies.

Authors:  Hugues Aschard; Sharon Lutz; Bärbel Maus; Eric J Duell; Tasha E Fingerlin; Nilanjan Chatterjee; Peter Kraft; Kristel Van Steen
Journal:  Hum Genet       Date:  2012-07-04       Impact factor: 4.132

4.  Application of a novel hybrid study design to explore gene-environment interactions in orofacial clefts.

Authors:  Oivind Skare; Astanand Jugessur; Rolv Terje Lie; Allen James Wilcox; Jeffrey Clark Murray; Astrid Lunde; Truc Trung Nguyen; Håkon Kristian Gjessing
Journal:  Ann Hum Genet       Date:  2012-05       Impact factor: 1.670

5.  A polytomous conditional likelihood approach for combining matched and unmatched case-control studies.

Authors:  Mulugeta Gebregziabher; Paulo Guimaraes; Wendy Cozen; David V Conti
Journal:  Stat Med       Date:  2010-01-12       Impact factor: 2.373

6.  Case-only genome-wide interaction study of disease risk, prognosis and treatment.

Authors:  Brandon L Pierce; Habibul Ahsan
Journal:  Genet Epidemiol       Date:  2010-01       Impact factor: 2.135

  6 in total

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